---

name: pytorch-a2c-ppo-acktr-gail description: "Operate the PyTorch A2C/PPO/ACKTR/GAIL reinforcement-learning repository, including training commands, model components, GAIL demos, and troubleshooting." disable-model-invocation: true metadata: disco-role: operating license: MIT

pytorch-a2c-ppo-acktr-gail

Use this repo skill when a task involves the PyTorch implementation of A2C, PPO, ACKTR, and GAIL reinforcement-learning workflows, including Gym environment setup, training command construction, policy/rollout internals, checkpoint playback, or imitation-learning expert data.

Start Here

• Confirm the source/version baseline before relying on the skill: references/repo-provenance.md.
• For package install, import, dependency, Gym/PyBullet, CUDA, and stale-flag issues, read references/troubleshooting.md.
• For shared parser flags, command conventions, and source-script mapping, read references/cli-and-config-reference.md.
• For checkpoints, monitor logs, historical result artifacts, and expert-data artifacts, read references/data-and-artifacts.md.
• Run scripts/check_install.py for a safe import/API smoke check after installing the package.

Sub-skill Routes

Task	Load
Build or debug A2C/PPO/ACKTR training commands, evaluation intervals, checkpoint playback, Gym environment wrappers, or long-run experiment settings.	sub-skills/training-workflows/SKILL.md
Inspect or modify Policy, CNNBase, MLPBase, distributions, RolloutStorage, A2C_ACKTR, PPO, KFAC, schedules, or tensor-shape behavior.	sub-skills/model-components/SKILL.md
Convert expert demonstrations, validate GAIL HDF5/.pt formats, use ExpertDataset, or explain Discriminator/--gail behavior.	sub-skills/gail-imitation/SKILL.md

Minimal Public Setup

This is an older Gym/PyTorch codebase. A practical environment needs the package, PyTorch, Gym, Stable-Baselines3 wrapper utilities, PyBullet support if using Bullet envs, Matplotlib, and h5py for GAIL files.

pip install -e .
pip install h5py
python - <<'PY'
import a2c_ppo_acktr
from a2c_ppo_acktr.model import Policy
from a2c_ppo_acktr.storage import RolloutStorage
print('import ok')
PY

If pybullet_envs fails with a Gym registry error, read references/troubleshooting.md before changing training code.

Safe Verification First

Do not start full Atari, MuJoCo, PyBullet, or GAIL training just to verify the setup. Prefer:

python scripts/check_install.py
python sub-skills/training-workflows/scripts/build_training_command.py --preset atari-ppo --env-name PongNoFrameskip-v4
python sub-skills/model-components/scripts/smoke_model_components.py
python sub-skills/gail-imitation/scripts/convert_gail_h5_to_pt.py --help

Only run long training after the user confirms the target environment, simulator dependencies, data availability, compute budget, and output directories.